A Base Pair Outside the Catalytic Core of the I‐R3 DNA Enzyme Has a Significant Effect on Its Cleavage Activity: An Improved Catalytic Core Model and an Automated Design Program
Bibliographic record
Abstract
The I‐R3 DNA enzyme, in its trans ‐acting form, is capable of cleaving single‐stranded DNA (ssDNA) molecules. We have collected all published information on the activity levels of the original I‐R3 DNA enzyme and its known variants and embedded that information into a program (we called IR3 ). The program was applied to the sequences of a set of ssDNA viruses and identified all potential catalytic core substrates (targets) and output optimal I‐R3 DNA enzyme sequences for all the targets, along with expected activity levels of the enzymes at those targets. Upon experimentally measuring the in vitro cleavage activities of the I‐R3 variants, we found marked differences between the program‐predicted and experimentally measured values. This demonstrated the incompleteness of the I‐R3 model: The sequence of the nucleotides of the catalytic core is not sufficient to fully determine its activity level. A set of experiments was carried out in which the effect of all possible combinations of Watson–Crick base pairs at two positions near the catalytic core, termed S I and S II , was tested. To confirm a newly formed hypothesis, the nucleotide at the S II position of the enzyme strand was mutated to a G and a T, with the substrate strand mutated accordingly. In every case, this led to an increase in relative activity when changed to a G and a decrease, when changed to a T, of the variant I‐R3 DNA enzyme. Clearly, the discovered base pair peripheral to the catalytic core has a substantial effect on cleavage activity. This improves the current model of essential nucleotides, and the IR3 software outputs I‐R3 enzyme‐sequence recommendations that make them more likely to cleave their targets. The software is available for download at https://github.com/XinxinTree/IR3.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".